High-resolution geophysical parameter information, as it can be provided,
for example, by crosshole georadar and seismic tomography, has proven
to provide useful spatial information to complement traditional hydrological
methods such as core analyses, logging techniques, and tracer or
pumping tests. Quantitative integration of these diverse database
components is one of the major challenges in the field of high-resolution
hydrogeophysics because of their different scales of measurement
and the usually weak petrophysical relations among the measurements.
In this study, we systematically explore the usefulness of a conditional
stochastic simulation approach based on simulated annealing for this
purpose. First, we generate a realistic model of an alluvial aquifer
consisting of a 2D scale-invariant porosity field. On the basis of
this model, we generate synthetic neutron porosity logs and crosshole
georadar tomographic surveys. We then use the proposed geostatistical
simulation approach to integrate this hydrogeophysical database.
The effectiveness of this approach to characterize the detailed porosity
distribution in heterogeneous alluvial aquifers is assessed by comparing
the results for a variety of simulated porosity fields that differ
fundamentally in terms of their conditioning information. Our results
indicate this approach has the potential to allow for a realistic
hydrogeophysical characterization in the submeter range of the porosity
distribution in heterogeneous alluvial aquifers.